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Found 55 Skills
Translates Snowflake dbt SQL models to Standardized BigQuery SQL. Handles SQL compilation, Jinja macro placeholder masking, BigQuery Translation Service migration workflows, AST-based config transformations, explicit type casting, JSON extraction standardization, and deduplication. Use when migrating Snowflake dbt pipelines or models to Google Cloud BigQuery. Don't use for generic BigQuery queries or non-Snowflake SQL migrations.
Install and initialize task-master for AI-powered task management and specification-driven development. Use this skill when users ask you to parse a new PRD, when starting a new project that needs structured task management, when users mention wanting task breakdown or project planning, or when implementing specification-driven development workflows.
AI-powered task management for structured, specification-driven development. Use this skill when you need to manage complex projects with PRDs, break down tasks into subtasks, track dependencies, and maintain organized development workflows across features and branches.
Vercel Connect expert guidance — securely obtain scoped OAuth tokens for third-party services (Slack, GitHub, MCP servers, OAuth, Snowflake) on behalf of apps or users via Vercel OIDC. Use when wiring up third-party API access, connecting to MCP servers, sending Slack messages, accessing GitHub APIs, receiving webhook events from Slack/Linear/GitHub and forwarding them to your agents and apps, or building Eve agent connections.
129 practical Oracle Database and Oracle Container Registry reference guides covering SQL/PL/SQL development, performance tuning (AWR, ASH, explain plan, indexes, wait events, memory), security (TDE, VPD, auditing, network), administration (RMAN, Data Guard, undo/redo, users), monitoring, architecture (RAC, CDB/PDB, Exadata, In-Memory, OCI), DevOps (Liquibase, Flyway, utPLSQL, EBR), migrations from Postgres/MySQL/SQL Server/MongoDB/Snowflake/Redshift/DB2, PL/SQL development (packages, cursors, collections, unit testing, debugging), Oracle features (AQ, DBMS_SCHEDULER, materialized views, APEX), SQLcl (basics, scripting, Liquibase, MCP server, CI/CD), ORDS (architecture, authentication, AutoREST, REST API design, PL/SQL gateway), and Oracle Container Registry images. Use for any Oracle DB question, ORA- errors, DBMS_ packages, v$ views, Oracle tooling, ORDS REST APIs, SQLcl commands, or Oracle container images. Always consult this skill before answering Oracle-specific questions.
Guides an end-to-end data-warehouse migration to Amazon Redshift — discovery, schema/SQL/stored-procedure/macro/script conversion, data migration, validation, performance comparison, and reporting. Source-routed via `references/<source>/`; Teradata (Vantage) is the supported source; additional sources are added as their own `references/<source>/` sets. Text-only knowledge (no executable code) — the AI generates all execution at runtime. Applies when a user wants to migrate Teradata to Amazon Redshift, convert Teradata DDL/SQL/stored procedures/macros/BTEQ to Redshift/RSQL, or assess Teradata-to-Redshift migration complexity. Applies only to migrations targeting Amazon Redshift; migrations to other platforms (Snowflake, BigQuery, Databricks, etc.) are out of scope regardless of source. Does not cover general Redshift administration, performance tuning, or troubleshooting of existing Redshift clusters (no migration involved), or sources not listed under references/.
Creates new Robot Framework test cases for SnapLogic pipeline testing. Use when the user wants to create a new test file, add test cases to existing files, or needs test templates for specific system types (Oracle, PostgreSQL, Snowflake, etc.).
Cloud & AI FinOps advisory skill. Structured cost optimization using the FinOps Foundation framework. Covers AWS, Azure, GCP, OCI, AI inference, and data platforms (Databricks, Snowflake). Use for: cloud costs, cost optimization, cloud spend, AI costs, cloud bill, FinOps assessment, GreenOps, right-sizing, commitment strategy, tagging governance.
Connect Spice to data sources and query across them with federated SQL. Use when connecting to databases (Postgres, MySQL, DynamoDB), data lakes (S3, Delta Lake, Iceberg), warehouses (Snowflake, Databricks), files, APIs, or catalogs; configuring datasets; creating views; writing data; or setting up cross-source queries.
Write optimized SQL for your dialect with best practices. Use when translating a natural-language data need into SQL, building a multi-CTE query with joins and aggregations, optimizing a query against a large partitioned table, or getting dialect-specific syntax for Snowflake, BigQuery, Postgres, etc.
Plan a migration onto MotherDuck. Use when moving from Snowflake, Redshift, PostgreSQL, dbt-heavy stacks, or lakehouse tooling and the key decisions are target pattern, cutover slices, validation, rollback, and native-versus-DuckLake posture.
Transition from static LLM chats to autonomous agents that execute multi-step tasks. Use this when you need to automate cross-platform reports (e.g., Snowflake to Google Docs), build self-service tools for non-technical teams, or create "anticipatory" engineering workflows that draft PRs based on Slack discussions.